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    Item type:Publication,
    Visualizing Political Communication Trends across Generations on X (Twitter): Insights Through Topic Modeling and Word Clouds
    (2024-01-01)
    Udomwisanpat, Prinwat
    ;
    Jitkajornwanich, Kulsawasd
    ;
    Kraishan, Obada
    ;
    Srestasatheirn, Panu
    ;
    Lawawirojwong, Siam
    This study examines the interests and significance of words on Twitter (or X) across different generational groups: Baby Boomers, Generation X, Generation Y, and Generation Z. Using Topic Modeling with Latent Dirichlet Allocation (LDA), the research explores relationships and word importance within each group. As the results of topic modeling are not always easy to interpret, we used word cloud visualization to help make sense of the results for each generation. The findings reveal distinct patterns: Baby Boomers frequently mention print media, news websites, and prominent Thai political figures; Generation X emphasizes individuals and local political issues in Bangkok; Generation Y discusses political and social events; and Generation Z uniquely questions political and social activities. This research methodology is applicable across languages and tasks, offering insights into generational behaviors and interests.
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    Analysis of Shopping Mall Tourist Satisfaction in Bangkok Using Word Cloud of Online Reviews
    (2023-01-01)
    Ladkoom, Kobthong
    ;
    Tarigan, Emiya Fefayosa Br
    ;
    Yasirandi, Rahmat
    ;
    Suwastika, Novian Anggis
    ;
    Anom, Rahmat Indra Pratama
    The tourism industry is very important to prioritize, especially for developing countries like Thailand. The increase in tourist visits to Bangkok also triggers the potential for a rise in Bangkok tourism during the pandemic. In this study, shopping malls are one of the attractive attractions for a capital city like Bangkok. Tourist expectations of attraction must be realized so that satisfaction can be realized and created revisit. In the digitalization era, the internet's use to find and disseminate information has become commonplace. Tripadvisor.com is one of the leading review sites, which already has many reviewers, and is the case study in this research. Using Word Cloud as an analysis technique and clustering of data reviews, several important factors influence tourist satisfaction. Based on the 1186 clustered reviewers, several factors were produced, such as Place Quality, Location Access, Support Facilities, Price, and Seller Attitude. These factors can influence the decision to visit shopping malls in Bangkok because they represent tourist satisfaction.